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Estimation in large and disaggregated demand systems: an estimator for conditionally linear systems

  • Richard Blundell

    (Dept. of Economics, University College -  GB, Institute for Fiscal Studies)

  • Jean-Marc Robin

    (Laboratoire d'Economie Appliquée, INRA)

Empirical demand systems that do not impose unreasonable restrictions on preferences are typically non-linear. We show, however, that all popular systems possess the property of conditional linearity. A computationally attractive iterated linear least squares estimator (ILLE) is proposed for large non-linear simultaneous equation systems which are conditionally linear in unknown parameters. The estimator is shown to be consistent and its asymptotic efficiency properties are derived. An application is given for a 22-commodity quadratic demand system using household-level data from a time series of repeated cross-sections.

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Paper provided by Institut National de la Recherche Agronomique, France in its series Working Papers with number 249982.

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Length: 209-232
Date of creation: 1999
Date of revision:
Publication status: Published in Journal of Applied Econometrics
Handle: RePEc:inr:wpaper:249982
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